Nomogram predictive model of post-operative recurrence in non-functioning pituitary adenoma

Background: To analyze and predict the possibility of post-operative recurrence in non-functioning pituitary adenoma (NFPA) patients, we investigated the clinical factors leading to tumor recurrence and built a nomogram predictive model based on these risk factors. Methods: A single-center retrospective study was performed. A total of 145 NFPA patients who underwent surgical treatment at Shenzhen People's Hospital from September 2013 to January 2019 were selected. Among them, 52 patients were diagnosed with recurrence of NFPA according to follow-up investigations. Binary logistic regression analysis was used to determine the significant risk factors. A nomogram model was then built to predict recurrence using these factors. Results: The univariate analysis and the binary logistic regression analysis showed that age, tumor size, cavernous invasion, sphenoid sinus invasion, and surgical extension were significant factors affecting tumor recurrence. We then built a nomogram model to predict post-operative recurrence in NFPA patients using these factors. The correlation analysis indicated that sphenoid sinus invasion [hazard ratio (HR) = 13.14, 95% confidence interval (CI): 7.03-24.58, P<0.0001], cavernous sinus invasion (HR = 7.53, 95% CI: 4.27-13.28, P<0.0001), and tumor size (HR = 11.06, 95% CI: 6.11-20.03, P<0.0001) could promote the recurrence of NFPA. In contrast, advanced age (HR = 0.50, 95% CI: 0.28-0.86, P<0.0001) and gross total resection (HR = 0.12, 95% CI: 0.07-0.22, P<0.0001) could effectively inhibit recurrence. Conclusions: In this study, we developed a nomogram predictive model based on the significant recurrence-associated factors for NFPA. This nomogram may aid neurosurgeons in the post-operative prediction of recurrence, and may facilitate tailored counseling of individual patients.